Fruit internal quality evaluation using on-line nuclear magnetic resonance sensors

An on-line nuclear magnetic resonance (NMR) quality evaluation sensor was designed, constructed and tested. The device consists of a superconducting magnet with a 20 mm diameter surface coil and a 150 mm diameter imaging coil coupled to a conveyor system. The conveyor was run at speeds ranging from 0 to 250 mm/s. The NMR spectra of avocado fruits and one-dimensional magnetic resonance images of fresh cherries were acquired while the fruits were moving on a conveyor bet. The NMR spectra were used to measure the oil/water ratio in avocados and this ratio correlated to percent dry weight, the correlation coefficient varied between 0.97 and 0.89 and decreased with increasing speed. One-dimensional magnetic resonance images of cherries were used to detect the presence of pits in cherries. Different belt speeds (up to 250 mm/s) were used and results of the pit detection tests were compared with static measurements. Higher classification errors occurred under static conditions as compared to dynamic conditions. An algorithm based on the change in shape of the one-dimensional image between a cherry with and without a pit yielded good classification of the fruits under static and dynamic conditions.